Search Results (3,021)

High-salinity water environments, e.g., saline lacustrine basins and lagoons, represent significant sedimentary settings on Earth. They serve not only as crucial archives of paleoclimate and paleoenvironmental evolution but also as favorable realms for the development of high-quality hydrocarbon source rocks. Although traditional views suggested that high salinity inhibits biological activity and is thus detrimental to source rock formation; recent hydrocarbon discoveries in formations such as the Leikoupo Formation (Sichuan Basin) and Majiagou Formation (Ordos Basin) in China have confirmed the exceptional hydrocarbon generation potential of source rocks in such settings. Focusing on major sedimentary basins in China, this review synthesizes how high-salinity settings critically control the integrated “generation-storage” sequence of hydrocarbon source rocks. Research indicates that moderate salinity can promote blooms of halophilic microorganisms, e.g., algae, cyanobacteria, resulting in high primary productivity. Concurrently, salinity-driven stable water stratification creates a strongly reducing bottom water environment, which greatly facilitates the preservation of organic matter, establishing a synergistic enrichment model of “high productivity—excellent preservation.” Products of high-salinity environments, such as evaporites, e.g., gypsum, halite, can act as catalysts, lowering the activation energy for hydrocarbon generation and enhancing hydrocarbon yield. Additionally, associated organic salts provide supplementary material for hydrocarbon generation. Regarding reservoir quality, the laminated structures formed in high-salinity settings, combined with organic–inorganic synergistic diagenesis, e.g., dolomitization, organic acid dissolution, and hydrocarbon-generation overpressure, collectively shape high-quality reservoirs with significant heterogeneity. Despite important progress, challenges remain, including the quantitative analysis of primary factors controlling organic matter enrichment, the threshold of salinity inhibiting biological communities, and the prediction of strongly heterogeneous reservoirs. Saline settings serve as critical carbon sinks in the geological carbon cycle through high primary productivity, enhanced preservation conditions, and distinctive mineral assemblages, playing a particularly important role in the formation of hydrocarbon source rocks and long-term carbon sequestration. Future research should integrate modern saline lake observations with high-resolution characterization techniques to deepen the understanding of the formation mechanisms of high-salinity source rocks, aiming to provide theoretical guidance and exploration targets for petroleum systems in similar geological settings worldwide. Full article

Environmental metagenomics and microbial taxonomy provide essential frameworks to evaluate how population structures shape the evolution of antimicrobial resistance and microbial community dynamics within densely populated environments. To evaluate microbial community composition and pathogenic potential, high-touch surfaces at high-traffic sites on and off campus were analyzed using metagenomics and characterization of 188 bacterial isolates, including antibiotic susceptibility testing, hemolytic assays, and whole-genome sequencing. Off-campus sites showed significantly higher bacterial richness and more complex communities enriched with diverse potential pathogens. Notably, high-risk carbapenemase genes were predominantly identified in these off-campus urban environments. In contrast, on-campus environments harbored less diverse communities dominated by opportunistic, antibiotic-resistant Staphylococcus species, with metagenomic analysis confirming a concentrated enrichment of β-lactam resistance determinants associated with methicillin-resistant staphylococci. Phenotypic profiling revealed extensive antimicrobial resistance, with 84.7% of isolates exhibiting resistance to at least one antibiotic and 35.1% of Staphylococcus showing hemolytic activity. Whole-genome sequencing further revealed that these resistance and pathogenic traits are predominantly localized on mobile plasmids, highlighting a high potential for horizontal gene transfer. These findings indicate that population activities shape distinct microbial communities in closely adjacent environments and highlight the importance of monitoring high-risk resistance determinants in densely populated university settings. Full article

Monitoring bird activity at public roosts is essential for understanding stopover behavior during migration, assessing ecological change, and supporting conservation strategies. Existing weather radar-based roost detection methods primarily rely on high-reflectivity ring-shaped echoes, which can lead to missed detections when roost-related echo structures are weak or indistinct. To address this limitation, this study proposes a saliency-constrained multi-peak spectral approach for monitoring and identifying public bird roosts using weather radar. At the radar resolution-cell scale, a saliency-constrained multi-peak Doppler spectrum decomposition and classification method is developed. Mixed Doppler power spectra are decomposed into multiple independent subpeaks through spectral peak saliency detection, and spectral polarimetric features are utilized to identify bird-related subpeaks, yielding a set of bird motion subgroups within each resolution cell. On this basis, a Bird Roost Index (BRI) is introduced, which couples the number of bird subgroups with their radial velocity dispersion to quantitatively characterize the complexity of bird motion modes in local airspace. Finally, the proposed method is applied to operational S-band weather radar observations collected over the Dongting Lake Basin roosts region during the spring season. The results demonstrate that the BRI exhibits strong spatial consistency and coherent temporal evolution, enabling robust characterization of communal roosting activity. This confirms the robustness of the proposed approach and highlights its potential for operational monitoring of migratory bird communal roosts using weather radar spectral data. Full article

Greece exhibits a continuous and exceptionally well-documented tradition of water management extending from prehistoric times to the modern era. This review critically examines the evolution of Greek hydro-technologies within their historical, environmental, and socio-political contexts, highlighting their enduring relevance to contemporary water resource management. Beginning with the advanced hydraulic systems of the Minoan civilization, the study traces the development, transformation, decline, and rediscovery of water management practices across successive periods, including the Mycenaean, Classical, Hellenistic, Roman, Byzantine, Venetian, Ottoman, and modern Greek eras. The analysis is based on a synthesis of archeological evidence, historical sources, and technical studies from approximately 200 documented sites throughout Greece. Particular emphasis is placed on water supply, drainage, sanitation, irrigation, and governance systems, as well as on periods during which hydraulic knowledge was partially lost and later reintroduced or adapted. Representative case studies illustrate the spatial and technological diversity of Greek hydro-technological solutions, ranging from monumental aqueducts and dams to decentralized cisterns, wells, and communal irrigation systems. The review demonstrates that Greek hydro-technologies consistently integrated technical innovation with environmental adaptation, social organization, and institutional regulation. This diachronic synthesis provides transferable lessons for modern water governance, infrastructure resilience, and climate adaptation, offering a conceptual framework for addressing contemporary challenges related to water scarcity, climate variability, and sustainable water management in Mediterranean and semi-arid regions. Full article

With the evolution of smart grids, power communication networks are increasingly required to support high-bandwidth and diversified services such as high-definition video, real-time control, and positioning—services that impose dual challenges of communication capacity and spectrum constraints—under severe resource limitations. Conventional orthogonal modulation schemes exhibit significant limitations in spectral efficiency and concurrent access capabilities, particularly in supporting high-density user environments. To address this, we propose a communication system based on non-orthogonal overlapped chirp modulation, in which the intrinsic symmetry properties of chirp waveforms are utilized to enhance system design and performance. We first construct the system architecture with a multi-symbol concurrent transmission scheme and introduce continuous orthogonal phase modulation to improve symbol distinguishability and mitigate inter-symbol interference—an approach that effectively harnesses signal symmetry for interference suppression. At the receiver, a low-complexity demodulation algorithm based on correlation matrix computation is developed, further improved through oversampling techniques that exploit temporal and spectral symmetry in signal design. Monte Carlo simulations confirm that the proposed system outperforms traditional orthogonal chirp and orthogonal frequency division multiplexing systems in bit error rate performance and spectral efficiency across varying signal-to-noise ratios and modulation schemes. The proposed NOOC system achieves spectral efficiency scaling linearly with concurrency level K, reaching up to 16 bits/s/Hz for K = 16 with BPSK, compared to 1 bit/s/Hz in orthogonal systems. The study provides both a theoretical foundation and practical insights for developing symmetry-aware, efficient, and reliable air interface technologies suitable for future power-private networks. Full article

This article presents a comparative analysis of divine kingship in two foundational Bronze Age civilizations: the Ur III Dynasty of Mesopotamia (ca. 2112–2004 BC) and the Shang Dynasty of China (ca. 1600–1046 BC). While both polities strategically adopted royal deification to consolidate authority within their territorial states, the underlying motivations, manifestations, and historical consequences diverged profoundly. In Ur III, king Šulgi’s self-deification was a deliberate political instrument, carefully constructed to centralize power and legitimize military expansion. This consolidation was performed explicitly through the use of the divine determinative in royal inscriptions, the establishment of state-sponsored cults with temples and statues for the living king, and the composition of royal hymns. In stark contrast, the kingship of the Shang Dynasty was a combination of divine power, clan power and military power. His authority was mediated through a monopoly on divination and ancestral communication, and expressed implicitly through ritual bronze vessels, royal tombs, and a cosmology that positioned the king at the center of the world. This study concludes that these distinct models—Ur III’s politically performative divinity versus Shang’s religio-kin-based sanctity—not only addressed contemporary crises of legitimacy but also predetermined subsequent political evolution, foreshadowing the Zhou Dynasty’s concept of virtuous governance and explaining the ultimate transience of divine kingship in both regions. Full article

This study examines the evolution of qualitative research in the Social Sciences and Arts & Humanities over time through an extensive bibliometric analysis of 15,115 publications indexed in Scopus between 1985 and 2026. This research maps the scope of the field, the most prevalent methodologies, types of publications, linguistic distribution, and geographical origin of the works. Simultaneously, it correlates qualitative, quantitative, and mixed methodologies, highlighting the tensions, differences, and synergies between them. Using PRISMA-guided selection and bibliometric techniques, the analysis revealed a gradual and steady increase in qualitative research over the last decade. In the Arts and Humanities, there is a particular emphasis on narrative research, discourse analysis, and ethnography, while in the Social Sciences, qualitative, quantitative, and mixed methodologies coexist more evenly, with case studies and semi-structured interviews being used extremely frequently. Analysis of the document types revealed the predominance of scientific articles (over 85%), with English being the main language of publication. In terms of geographical distribution, the US and the UK are the strongest producers of qualitative knowledge, with Australia and Canada contributing significantly and a gradual strengthening of the participation of research communities from Latin America and Asia. The data show that publications referring to qualitative and mixed methodologies demonstrate comparatively higher citation visibility within the analyzed corpus, particularly in education, culture, and public policy. The findings indicate that the qualitative approach continues to play a key role in understanding the complex and lived dimensions of human experience, while opportunities for more integrated hybrid methodological frameworks will emerge in the future—both within individual scientific fields and in their interconnections. This study provides one of the largest bibliometric mappings of qualitative research internationally and systematically clarifies how the qualitative tradition differs between the Social Sciences and the Arts & Humanities. The findings can be used for evidence-based curriculum design, targeted development of research collaborations, and formulation of publication policies that enhance the visibility and influence of qualitative research. Full article

U.S. urban industry has experienced remarkable transformations. At least two and a half centuries of evolution have changed location, productive processes, technology, sources of energy, and outputs. This article analyzes an attempt to help retrofit an aging urban industrial district in South Phoenix. It focuses specifically on mounting pressures to convert remaining, centrally located, industrial land to non-productive commercial and office uses. It is argued that the Wedge South Mountain industrial area presents advantages to the local community in terms of urban structure, proximity to labor pools, and good transport networks in the core of the Phoenix metropolis. The methods comprised an Advanced Urban Planning Studio at Arizona State University, multiple inventories and site visits, presentations, and feedback from guest speakers and economic development specialists at the City of Phoenix and at the Greater Phoenix Economic Council. The main policy recommendations are to preserve small-business activities, modernize neighborhoods along industrial park settings with green and environmental strategies (i.e., parasols and solar panels), and encourage growth in the technology manufacturing sector. The key finding is a series of implications for the retrofitting of other urban industrial areas in the Global North. Full article

From 4G to 5G to 6G, every few years, a new generation of data transmission technology emerges to meet the growing demand for faster and more efficient communication. Artificial intelligence, the Internet of Things and the increasing need for global connectivity are the key drivers of this evolution, pushing both research and industry toward ever-higher data rates. These advanced technologies already consume vast amounts of resources and energy, relying on high-tech nano-fabrication processes such as metal–organic chemical vapor deposition, dry etching, deposition and lithography, all of which typically occur in energy-intensive cleanroom environments. This study evaluates the epitaxy process of GaN on SiC for high-electron-mobility transistor (HEMT) devices and integrated circuits using life cycle assessment. GaN HEMTs offer high efficiency and excellent thermal conductivity, paving the way for reduced chip footprints for lower energy consumption. This analysis enables informed decision-making regarding sustainability by providing detailed data and interpretation of Fraunhofer IAF’s GaN-on-SiC HEMT technology. Full article

Achieving autonomous and reliable unmanned aerial vehicle (UAV) swarm applications requires a flexible and efficient communication network structure. Unfortunately, the high-speed movement of UAVs leads to drastic changes in wireless links and topology structures, posing significant challenges to reliable data transmissions. Geographic routing protocols exhibit better adaptability to highly dynamic network topologies and have garnered extensive attention in UAV networks. However, existing works did not effectively address the impact of factors such as link state fluctuations and routing holes on the performance of these protocols. To this end, by considering future evolution of link states, this paper proposes a reinforcement-learning-based geographic routing protocol (Evo-QGeo) and introduces a new routing hole bypass method. Thanks to the evaluation of future evolution of link states and the multihop optimization capability of reinforcement learning, the end-to-end packet reception rate of Evo-QGeo is improved by up to 11.81~44.61% compared to existing ones. Meanwhile, the energy consumption is reduced by up to 36.94~74.47%, the latency is reduced by up to 21.63~38.68%, and the end-to-end expected transmission count is reduced by up to19.60~26.10%. This makes Evo-QGeo more suitable for highly dynamic UAV networks. Full article

The rapid evolution of Generative AI (GenAI) has created the conditions for developing innovative solutions that disrupt all fields of human-related activities. Within the healthcare sector, numerous AI-driven applications have emerged, offering comprehensive health-related insights and addressing user questions in real time. Nevertheless, most of them use general-purpose Large Language Models (LLMs); consequently, the responses may not be as accurate as required in clinical settings. Therefore, the research community is adopting efficient architectures, such as Multi-Agent Systems (MAS) to optimize task allocation, reasoning processes, and system scalability. Most recently, the Model Context Protocol (MCP) has been introduced; however, very few applications apply this protocol within a healthcare MAS. Furthermore, Retrieval-Augmented Generation (RAG) has proven essential for grounding AI responses in verified clinical literature. This paper proposes a novel architecture that integrates these technologies to create an advanced Agentic Corrective RAG (CRAG) system. Unlike standard approaches, this method incorporates an active evaluation layer that autonomously detects retrieval failures and triggers corrective fallback mechanisms to ensure safety and accuracy. A comparative analysis was conducted for this architecture against Typical RAG and Cache-Augmented Generation (CAG), demonstrating that the proposed solution improves workflow efficiency and enables more accurate, context-aware interventions in healthcare. Full article

The rapid proliferation of distributed energy resources (DERs), including photovoltaics, wind power, battery energy storage, and electric vehicles, has transformed traditional power systems into highly decentralized and data-rich environments. Virtual power plants (VPPs) have emerged as a key mechanism for aggregating these heterogeneous assets and enabling coordinated control, market participation, and grid-support functions. Recent advances in artificial intelligence (AI) have further elevated the scalability, autonomy, and responsiveness of VPP operations. This paper presents a comprehensive review of AI for VPPs, organized around a taxonomy of machine learning, deep learning, reinforcement learning, and hybrid approaches, and examines how these methods map to core VPP functions such as forecasting, scheduling, market bidding, aggregation, and ancillary services. In parallel, we analyze enabling architectural frameworks—including centralized cloud, distributed edge, hybrid cloud–edge collaboration, and emerging 5G/LEO satellite communication infrastructures—that support real-time data exchange and scalable deployment of intelligent control. By integrating methodological, functional, and architectural perspectives, this review highlights the evolution of VPPs from rule-based coordination to intelligent, autonomous energy ecosystems. Key research challenges are identified in data quality, model interpretability, multi-agent scalability, cyber-physical resilience, and the integration of AI with digital twins and edge-native computation. These findings outline promising directions for next-generation intelligent VPPs capable of delivering secure, flexible, and self-optimizing DER aggregation at scale. Full article

The deep sea is characterized by unique and extreme habitats. The absence of light, high salinity, hydrostatic pressure, low temperature, and high competition led to the evolution of physiological and biochemical adaptations necessary for survival. Marine fungi represent a significant part of deep-sea microbial communities. Studying bathypelagic sediment fungi helps us to understand their little-known communities and ecology, as well as their metabolic potential and ecophysiological properties, which have applications in pharmaceutical biotechnologies and bioremediation protocols. During an oceanographic campaign off the coast of Toulon (France, northwest Mediterranean Sea) in October 2021, as part of the KM3NeT Project, the Hybrid Remotely Operated Vehicle (HROV) Ariane collected a composite sediment sample at a depth of 2417 m. The sediment was physically, geochemically and mycologically characterized. Culturable fungi were isolated, and vital fungal strains were identified morphologically and molecularly. A total of 17 strains were isolated and identified in pure culture. The major taxa belonged to the Penicillium, Aspergillus, and Cladosporium genera, but widespread species such as Wallemia sebi were also found. This study also paves the way for further research into the advantages and disadvantages of using HROV technology for mycological cultural investigations at prohibitive depths. Full article

Understanding the Holocene environmental history of desert landscapes in northern China contributes to elucidating the mechanisms driving desertification in the mid-latitudes of the Northern Hemisphere (NH). Based on a systematic and comparative analysis on integrated paleoclimatic data from both China and the international community, this paper reviews the environmental evolution history of the Alashan Plateau since the Holocene, drawing upon sedimentary and proxy records from three major sandy deserts on the plateau—the Badanjilin, Tenggeli, Wulanbuhe Deserts. The results indicate that the Alashan Plateau experienced generally humid conditions during the early and middle Holocene, characterized by the development of high-level lakes; in contrast, the late Holocene was marked by aridity and intensified aeolian activity. For the three deserts on the plateau, the environmental evolution of the Tenggeli Desert during the early Holocene diverges from that of the other two. Meanwhile, the mid-Holocene drought event in the Badanjilin Deserts remains debated, centering on whether its spatial scale was local or regional across the plateau. The driving mechanism of environmental evolution in the study area can be fundamentally understood through the atmospheric and oceanic circulation systems, combined with solar insolation in the middle latitudes of NH. This interplay is comprehensively reflected by the interactions between the westerlies and the East Asian summer monsoon (EASM) across different periods. Responses of the Alashan Plateau’s climate to global change involve the combined effects of multiple factors, including the Westerlies, the EASM, the Atlantic-Pacific-Ocean (APO) circulation anomalies, the ‘third polar’ environmental effect of the Qinghai–Tibet Plateau, and the hydrological influence of the Yellow River, etc. The Holocene environmental evolution history of the study area was primarily shaped by climate patterns characterized by cold-dry and cold–wet (or temperate-moist) regimes. Understanding these patterns may provide insights for forecasting future climate trends in the Alashan Plateau under current global warming. Full article

Advancements in earth observation technologies are ushering in the big data era, yet this potential is compromised by intrinsic challenges: inherent uncertainty, spatiotemporal heterogeneity, multi-scale character, and pervasive data gaps. Traditional methods often fail to address these issues within a single, coherent system. The main contributions of this review are to systematically establish the Remote Sensing Geostatistical Paradigm (RSGP) as a comprehensive, unified framework. Powered by its core theory, Bayesian Maximum Entropy (BME), RSGP is a broadly designed epistemic framework that transcends a mere conceptual reorganization of established methods. It addresses the above challenges by highlighting two pivotal concepts within a spatiotemporal random field: (1) uncertainty quantification via probabilistic soft data, which redefines observations as probability density functions, representing a fundamental epistemological shift from deterministic scalars to probabilistic entities, and provides a universal interface for rigorous assimilation of heterogeneous remote sensing or in situ observations and synergy with other computational models, such as machine learning; and (2) spatiotemporal structure exploitation, which integrates the underlying structure embedded in remote sensing data of natural attributes, moving beyond mere optical properties to incorporate a broader range of available spatiotemporal information, for robust estimation and mapping purposes. Furthermore, the evolution of key technologies is illustrated by using real-world application cases, guiding how to implement RSGP in terms of different scenarios. Finally, the paradigm’s features and limitations are discussed. This synthesis provides the remote sensing community with a robust foundation for uncertainty-aware analysis and multi-source integration, bridging geostatistical logic with next-generation AI-driven Earth observation. Full article